Journals

The Journal of Machine Learning in Finance is the definitive source of the latest approaches, innovations and applications in machine learning in institutional investment management.

The journal will cover cross-asset markets, across learning and data types, covering areas including risk management, execution and allocation frameworks, among other areas. The journal will be published bi-annually.

The journal’s editorial board will include quantitative finance professionals, data scientists, machine-learning professionals as well as academics specializing in finance and artificial intelligence. Tony Guida, author of Big Data and Machine Learning in Quantitative Investment, and Executive Director, Senior Quant Researcher, is Editorial Chair of The Journal of Machine Learning for Finance.